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Predictive Performance of the Methods of Restricted and Mixed Regression Estimators
Author(s) -
Toutenburg H.
Publication year - 1996
Publication title -
biometrical journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.108
H-Index - 63
eISSN - 1521-4036
pISSN - 0323-3847
DOI - 10.1002/bimj.4710380807
Subject(s) - linear regression , proper linear model , statistics , regression analysis , regression diagnostic , regression , mathematics , estimator , segmented regression , partial least squares regression , cross sectional regression , bayesian multivariate linear regression , factor regression model
This article considers the problem of simultaneous prediction of actual and average values of the study variable in a linear regression model when a set of linear restrictions binding the regression coefficients is available, and analyzes the performance properties of predictors arising from the methods of restricted regression and mixed regression besides least squares.